COMPMID-2685: [CL] Use Weights manager
Change-Id: Ia1818e6ecd9386e96378e64f14d02592fe3cdf0f
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1997
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h b/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h
index 43abb67..e4e6f07 100644
--- a/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h
+++ b/arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h
@@ -25,7 +25,9 @@
#define __ARM_COMPUTE_CLCONVERTFULLYCONNECTEDWEIGHTS_H__
#include "arm_compute/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h"
+#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/CL/ICLSimpleFunction.h"
+#include "arm_compute/runtime/ITransformWeights.h"
namespace arm_compute
{
@@ -54,5 +56,54 @@
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output, const TensorShape &original_input_shape, DataLayout data_layout);
};
+
+namespace weights_transformations
+{
+/** Basic function to run @ref CLConvertFullyConnectedWeightsKernel. */
+class CLConvertFullyConnectedWeightsManaged : public ITransformWeights
+{
+public:
+ //Inherited method override
+ void run() override
+ {
+ _output.allocator()->allocate();
+ _func.run();
+ _reshape_run = true;
+ }
+
+ //Inherited method override
+ void release() override
+ {
+ _output.allocator()->free();
+ }
+
+ //Inherited method override
+ ICLTensor *get_weights() override
+ {
+ return &_output;
+ }
+
+ //Inherited method override
+ uint32_t uid() override
+ {
+ return _uid;
+ }
+ /** Configures the @ref CLConvertFullyConnectedWeights function
+ *
+ * @param[in] input Source weights tensor info to convert. Data type supported: U8/S8/QASYMM8/U16/S16/U32/S32/F16/F32.
+ * @param[in] original_input_shape Shape of the original input tensor (the one entering fully connected layer).
+ * @param[in] data_layout The data layout the weights have been trained in.
+ */
+ void configure(const ICLTensor *input, const TensorShape &original_input_shape, DataLayout data_layout)
+ {
+ _func.configure(input, &_output, original_input_shape, data_layout);
+ }
+
+private:
+ static constexpr uint32_t _uid = 0x5;
+ CLTensor _output{};
+ CLConvertFullyConnectedWeights _func{};
+};
+} // namespace weights_transformations
} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLCONVERTFULLYCONNECTEDWEIGHTS_H__ */
diff --git a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
index d54304e..9512b22 100644
--- a/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
+++ b/arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h
@@ -64,6 +64,54 @@
static Status validate(const ITensorInfo *input, const ITensorInfo *output);
};
+namespace weights_transformations
+{
+/** Basic function to manage the reshape weights generated from @ref CLFullyConnectedLayerReshapeWeights */
+class CLFullyConnectedLayerReshapeWeightsManaged : public ITransformWeights
+{
+public:
+ //Inherited method override
+ void run() override
+ {
+ _output.allocator()->allocate();
+ _func.run();
+ _reshape_run = true;
+ }
+
+ //Inherited method override
+ void release() override
+ {
+ _output.allocator()->free();
+ }
+
+ //Inherited method override
+ ICLTensor *get_weights() override
+ {
+ return &_output;
+ }
+
+ //Inherited method override
+ uint32_t uid() override
+ {
+ return _uid;
+ }
+
+ /** Configures the @ref CLFullyConnectedLayerReshapeWeights function
+ *
+ * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32.
+ */
+ void configure(const ICLTensor *input)
+ {
+ _func.configure(input, &_output);
+ }
+
+private:
+ static constexpr uint32_t _uid = 0x0;
+ CLTensor _output{};
+ CLFullyConnectedLayerReshapeWeights _func{};
+};
+} // namespace weights_transformations
+
/** Basic function to compute a Fully Connected layer on OpenCL. This function calls the following OpenCL kernels:
*
* -# @ref CLIm2ColKernel (called when the input comes from a convolutional layer)
@@ -130,25 +178,28 @@
void configure_conv_fc(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, bool retain_internal_weights);
void configure_mm(const ICLTensor *input, const ICLTensor *weights, ICLTensor *output, bool retain_internal_weights);
- MemoryGroup _memory_group;
- CLConvertFullyConnectedWeights _convert_weights;
- CLFlattenLayer _flatten_layer;
- CLFullyConnectedLayerReshapeWeights _reshape_weights_kernel;
- CLGEMM _mm_gemm;
- CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
- CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
- CLGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; // TODO(COMPMID-1889): Use CLGEMM to add bias in CLFullyConnectedLayer
- CLTensor _flatten_output;
- CLTensor _gemmlowp_output;
- CLTensor _converted_weights_output;
- CLTensor _reshape_weights_output;
- bool _are_weights_converted;
- bool _are_weights_reshaped;
- bool _is_fc_after_conv;
- bool _accumulate_biases;
- bool _is_quantized;
- bool _is_prepared;
- const ICLTensor *_original_weights;
+ MemoryGroup _memory_group;
+ IWeightsManager *_weights_manager;
+ CLConvertFullyConnectedWeights _convert_weights;
+ weights_transformations::CLConvertFullyConnectedWeightsManaged _convert_weights_managed;
+ weights_transformations::CLFullyConnectedLayerReshapeWeightsManaged _reshape_weights_managed_function;
+ CLFlattenLayer _flatten_layer;
+ CLFullyConnectedLayerReshapeWeights _reshape_weights_function;
+ CLGEMM _mm_gemm;
+ CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
+ CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
+ CLGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel; // TODO(COMPMID-1889): Use CLGEMM to add bias in CLFullyConnectedLayer
+ CLTensor _flatten_output;
+ CLTensor _gemmlowp_output;
+ CLTensor _converted_weights_output;
+ CLTensor _reshape_weights_output;
+ bool _are_weights_converted;
+ bool _are_weights_reshaped;
+ bool _is_fc_after_conv;
+ bool _accumulate_biases;
+ bool _is_quantized;
+ bool _is_prepared;
+ const ICLTensor *_original_weights;
};
} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLFULLYCONNECTEDLAYER_H__ */
diff --git a/arm_compute/runtime/CL/functions/CLGEMM.h b/arm_compute/runtime/CL/functions/CLGEMM.h
index b8e5fa6..3691fe9 100644
--- a/arm_compute/runtime/CL/functions/CLGEMM.h
+++ b/arm_compute/runtime/CL/functions/CLGEMM.h
@@ -32,12 +32,62 @@
#include "arm_compute/runtime/CL/CLTensor.h"
#include "arm_compute/runtime/IFunction.h"
#include "arm_compute/runtime/IMemoryManager.h"
+#include "arm_compute/runtime/IWeightsManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
namespace arm_compute
{
class ICLTensor;
+namespace weights_transformations
+{
+/** Basic function to manage the reshape weights generated from @ref CLGEMMReshapeRHSMatrixKernel */
+class CLGEMMReshapeRHSMatrixKernelManaged : public ITransformWeights
+{
+public:
+ //Inherited method override
+ void run() override
+ {
+ _output.allocator()->allocate();
+ CLScheduler::get().enqueue(_kernel, false);
+ _reshape_run = true;
+ }
+
+ //Inherited method override
+ void release() override
+ {
+ _output.allocator()->free();
+ }
+
+ //Inherited method override
+ ICLTensor *get_weights() override
+ {
+ return &_output;
+ }
+
+ //Inherited method override
+ uint32_t uid() override
+ {
+ return _uid;
+ }
+
+ /** Configures the @ref CLGEMMReshapeRHSMatrixKernel kernel
+ *
+ * @param[in] input Input tensor. Data types supported: U8/S8/QASYMM8/U16/S16/F16/U32/S32/F32
+ * @param[in] info RHS matrix information to be used for reshaping.
+ */
+ void configure(const ICLTensor *input, GEMMRHSMatrixInfo info)
+ {
+ _kernel.configure(input, &_output, info);
+ }
+
+private:
+ static constexpr uint32_t _uid = 0x15;
+ CLTensor _output{};
+ CLGEMMReshapeRHSMatrixKernel _kernel{};
+};
+} // namespace weights_transformations
+
/** Basic function to execute GEMM on OpenCL. This function calls the following OpenCL kernels:
*
* -# @ref CLGEMMReshapeLHSMatrixKernel (only if the RESHAPED_V1 is selected by the heuristic model)
@@ -52,9 +102,10 @@
public:
/** Default constructor.
*
- * @param[in] memory_manager (Optional) Memory manager.
+ * @param[in] memory_manager (Optional) Memory manager.
+ * @param[in] weights_manager (Optional) Weights manager.
*/
- CLGEMM(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+ CLGEMM(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMM(const CLGEMM &) = delete;
/** Default move constructor */
@@ -123,18 +174,20 @@
static Status validate_reshaped_v2(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
static Status validate_reshaped_only_rhs(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *c, const ITensorInfo *output, float alpha, float beta, const GEMMInfo &gemm_info);
- MemoryGroup _memory_group;
- CLGEMMMatrixMultiplyKernel _mm_kernel;
- CLGEMMReshapeLHSMatrixKernel _reshape_lhs_kernel;
- CLGEMMReshapeRHSMatrixKernel _reshape_rhs_kernel;
- CLGEMMMatrixMultiplyReshapedKernel _mm_reshaped_kernel;
- CLGEMMMatrixMultiplyReshapedOnlyRHSKernel _mm_reshaped_only_rhs_kernel;
- CLTensor _tmp_a;
- CLTensor _tmp_b;
- const ICLTensor *_original_b;
- bool _reshape_b_only_on_first_run;
- bool _is_prepared;
- GEMMType _gemm_type;
+ MemoryGroup _memory_group;
+ IWeightsManager *_weights_manager;
+ CLGEMMMatrixMultiplyKernel _mm_kernel;
+ CLGEMMReshapeLHSMatrixKernel _reshape_lhs_kernel;
+ CLGEMMReshapeRHSMatrixKernel _reshape_rhs_kernel;
+ weights_transformations::CLGEMMReshapeRHSMatrixKernelManaged _reshape_rhs_kernel_managed;
+ CLGEMMMatrixMultiplyReshapedKernel _mm_reshaped_kernel;
+ CLGEMMMatrixMultiplyReshapedOnlyRHSKernel _mm_reshaped_only_rhs_kernel;
+ CLTensor _tmp_a;
+ CLTensor _tmp_b;
+ const ICLTensor *_original_b;
+ bool _reshape_b_only_on_first_run;
+ bool _is_prepared;
+ GEMMType _gemm_type;
};
} // namespace arm_compute
diff --git a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
index 0b27c82..017bf78 100644
--- a/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLGEMMConvolutionLayer.h
@@ -39,6 +39,8 @@
#include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h"
#include "arm_compute/runtime/CL/functions/CLReshapeLayer.h"
#include "arm_compute/runtime/IMemoryManager.h"
+#include "arm_compute/runtime/ITransformWeights.h"
+#include "arm_compute/runtime/IWeightsManager.h"
#include "arm_compute/runtime/MemoryGroup.h"
#include <memory>
@@ -82,6 +84,59 @@
CLWeightsReshapeKernel _weights_reshape_kernel;
};
+namespace weights_transformations
+{
+/** Basic function to manage the reshape weights generated from @ref CLConvolutionLayerReshapeWeights */
+class CLConvolutionLayerReshapeWeightsTransform : public ITransformWeights
+{
+public:
+ /** Configures the @ref CLConvolutionLayerReshapeWeights function
+ *
+ * @param[in] input Input tensor. Data type supported: QASYMM8/F16/F32.
+ * @param[in] biases Biases tensor. Data type supported: Same as @p input.
+ * @param[in] num_groups Number of groups when performing a grouped convolution.
+ */
+ void configure(const ICLTensor *input, const ICLTensor *biases, unsigned int num_groups)
+ {
+ _bias_bit = (biases != nullptr) ? 1 : 0;
+ _num_groups = num_groups;
+ _func.configure(input, biases, &_output, num_groups);
+ }
+
+ //Inherited method override
+ void run() override
+ {
+ _output.allocator()->allocate();
+ _func.run();
+ _reshape_run = true;
+ }
+
+ //Inherited method override
+ ICLTensor *get_weights() override
+ {
+ return &_output;
+ }
+
+ //Inherited method override
+ void release() override
+ {
+ _output.allocator()->free();
+ }
+
+ //Inherited method override
+ uint32_t uid() override
+ {
+ return ((0x9) | (_bias_bit << 7) | (_num_groups << 8));
+ }
+
+private:
+ CLTensor _output{};
+ CLConvolutionLayerReshapeWeights _func{};
+ int32_t _bias_bit{ 0 };
+ unsigned int _num_groups{ 0 };
+};
+} // namespace weights_transformations
+
/** Basic function to compute the convolution layer. This function calls the following OpenCL kernels/functions:
*
* -# @ref CLIm2ColKernel
@@ -96,9 +151,10 @@
public:
/** Constructor
*
- * @param[in] memory_manager (Optional) Memory manager.
+ * @param[in] memory_manager (Optional) Memory manager.
+ * @param[in] weights_manager (Optional) Weights manager.
*/
- CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
+ CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr, IWeightsManager *weights_manager = nullptr);
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMConvolutionLayer(const CLGEMMConvolutionLayer &) = delete;
/** Default move constructor */
@@ -186,13 +242,15 @@
int gemm_3d_depth, bool skip_im2col, const ActivationLayerInfo &act_info);
private:
- MemoryGroup _memory_group;
- CLConvolutionLayerReshapeWeights _reshape_weights;
- CLIm2ColKernel _im2col_kernel;
- CLGEMM _mm_gemm;
- CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
- CLCol2ImKernel _col2im_kernel;
- CLActivationLayer _activationlayer_function;
+ MemoryGroup _memory_group;
+ IWeightsManager *_weights_manager;
+ CLConvolutionLayerReshapeWeights _reshape_weights;
+ weights_transformations::CLConvolutionLayerReshapeWeightsTransform _reshape_weights_managed;
+ CLIm2ColKernel _im2col_kernel;
+ CLGEMM _mm_gemm;
+ CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
+ CLCol2ImKernel _col2im_kernel;
+ CLActivationLayer _activationlayer_function;
const ICLTensor *_original_weights;